On-the-go thermal imaging for water status assessment in commercial vineyards

The goal of this work was the assessment of commercial vineyard water status using on-the-go thermal imaging. On-the-go thermal imaging acquisition was conducted with a thermal camera operating at 1.20 m distance from the canopy, mounted on a quad moving at 5 km/h. Canopy temperature, cross water stress index (CWSI) and stomatal conductance index (Ig) were strongly and significantly correlated to stem water potential (Ψstem) in east and west side of the canopy. For CWSI, the values of the coefficient of determination (R2) were 0.88*** and 0.73*** for east and west sides, respectively. As regards the index Ig, its relationships with Ψstem showed R2=0.89*** and R2=0.77*** for east and west sides, respectively. These results are promising and evidence the potential of on-the-go thermal imaging to become a new tool to evaluate the vineyard water status.

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Leveraging Very-High Spatial Resolution Hyperspectral and Thermal UAV Imageries for Characterizing Diurnal Indicators of Grapevine Physiology

Remote Sensing ◽

10.3390/rs12193216 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3216 ◽

Cited By ~ 1

Author(s):

Matthew Maimaitiyiming ◽

Vasit Sagan ◽

Paheding Sidike ◽

Maitiniyazi Maimaitijiang ◽

Allison J. Miller ◽

...

Keyword(s):

Canopy Temperature ◽

Crop Productivity ◽

In Situ Measurements ◽

Sensor Technology ◽

Stress Index ◽

Coefficient Of Determination ◽

Neural Net ◽

Water Stress Index ◽

Very High

Efficient and accurate methods to monitor crop physiological responses help growers better understand crop physiology and improve crop productivity. In recent years, developments in unmanned aerial vehicles (UAV) and sensor technology have enabled image acquisition at very-high spectral, spatial, and temporal resolutions. However, potential applications and limitations of very-high-resolution (VHR) hyperspectral and thermal UAV imaging for characterization of plant diurnal physiology remain largely unknown, due to issues related to shadow and canopy heterogeneity. In this study, we propose a canopy zone-weighting (CZW) method to leverage the potential of VHR (≤9 cm) hyperspectral and thermal UAV imageries in estimating physiological indicators, such as stomatal conductance (Gs) and steady-state fluorescence (Fs). Diurnal flights and concurrent in-situ measurements were conducted during grapevine growing seasons in 2017 and 2018 in a vineyard in Missouri, USA. We used neural net classifier and the Canny edge detection method to extract pure vine canopy from the hyperspectral and thermal images, respectively. Then, the vine canopy was segmented into three canopy zones (sunlit, nadir, and shaded) using K-means clustering based on the canopy shadow fraction and canopy temperature. Common reflectance-based spectral indices, sun-induced chlorophyll fluorescence (SIF), and simplified canopy water stress index (siCWSI) were computed as image retrievals. Using the coefficient of determination (R2) established between the image retrievals from three canopy zones and the in-situ measurements as a weight factor, weighted image retrievals were calculated and their correlation with in-situ measurements was explored. The results showed that the most frequent and the highest correlations were found for Gs and Fs, with CZW-based Photochemical reflectance index (PRI), SIF, and siCWSI (PRICZW, SIFCZW, and siCWSICZW), respectively. When all flights combined for the given field campaign date, PRICZW, SIFCZW, and siCWSICZW significantly improved the relationship with Gs and Fs. The proposed approach takes full advantage of VHR hyperspectral and thermal UAV imageries, and suggests that the CZW method is simple yet effective in estimating Gs and Fs.

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On the use of different approaches based on photochemical reflectance index and surface temperature to monitor the water status of winter wheat in semi-arid regions

10.5194/egusphere-egu2020-14106 ◽

2020 ◽

Author(s):

Zoubair Rafi ◽

Valérie Le Dantec ◽

Olivier Merlin ◽

Said Khabba ◽

Patrick Mordelet ◽

...

Keyword(s):

Water Stress ◽

Winter Wheat ◽

Surface Temperature ◽

Water Status ◽

Stress Index ◽

Coefficient Of Determination ◽

Temperature Index ◽

Water Stress Index ◽

Semi Arid

Agriculture is considered to be the human activity that consumes the most mobilized water on a global scale. However, crops planted in semi-arid areas regularly face periods of moderate to extreme water stress. Such water stress periods have a considerable impact on the seasonal yield of these crops. In order to participate in a more rational irrigation water management, monitoring of the rapid changes in plant water status is necessary. For this purpose, the combination of two different wavelength ranges will be explored : an index based on Xanthophyll cycle (Photochemical Reflectance Index, PRI) and a commonly-used index from thermal infrared spectral range (LST). An experiment on winter wheat was carried out over two agricultural campaigns (2016 to 2018) in the Haouz basin, which is located in the Marrakech region, to better assimilate the temporal dynamics of PRI and surface temperature. In this study, four different approaches are proposed to study the functioning of wheat : 1- an approach based on solar angle to remove the structure effect (PRI0) from the PRI signal and to derive a water stress index PRIj, 2- an approach based on global radiation (Rg) to extrapolate a theoretical PRI (PRIth) for Rg equal to zero and to calculate a water stress index PRIlin, 3- an approach that determines an optimal PRI (PRIpot) on the basis of the available water content (AWC) criterion in order to derive a stress index I-PRI and 4- an energy balance approach to extract dry and wet surface temperatures in order to establish a normalized surface temperature index (Tnorm). The results of this work show a strong correlation between the PRI0 and the Leaf Area Index with a coefficient of determination equal to 0.92, indicating that it is possible to isolate the structural effects of wheat on the PRI signal. In addition, over the range of variation in AWC, a significant correlation with PRIj, PRIjlin and I-PRI was observed with coefficients of determination of 0.71, 0.42 and 0.24, respectively. In contrast to the Tnorm, which varies only for values of AWC below 30%, a coefficient of determination of 0.22 is obtained. Finally, the PRI allows us to acquire early and complete information on the response of wheat to change in AWC as opposed to the surface temperature index, revealing the potential of the PRI to monitor the water status of plants and their responses to changing environmental conditions.

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A new Remote Sensing-based vegetation water stress index: -Temperature Vegetation Water Stress Index (TVWSI)

10.5194/egusphere-egu2020-12308 ◽

2020 ◽

Author(s):

Rakesh Chandra Joshi ◽

Dongryeol Ryu ◽

Gary J. Sheridan ◽

Patrick N.J. Lane

Keyword(s):

Water Stress ◽

Water Status ◽

Canopy Temperature ◽

Stress Index ◽

Spectral Space ◽

Water Stress Index ◽

Water Stress Condition ◽

Forested Areas ◽

Vegetation Water ◽

Canopy Water

Remote sensing techniques are widely used to evaluate the biophysical status of vegetation, including water stress caused by soil water deficit. Based on the nominal links between water stress condition, transpiration and canopy temperature in the vegetation, numerous studies have used a trapezoidal relationship between Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) over vegetated surfaces to develop the water stress metric, in which the level of stress could be identified by the spatial location of the pixels on the spectral space (Goetz and Goetz 1997; Lambin, Lambin, and Ehrlich 1996; Nemani et al. 1993; Nemani and Running 1989; Price 1990; Sandholt, Rasmussen, and Andersen 2002). However, the amount of change in canopy temperature could also vary spatially by the canopy water status at that time. Thus, LST-NDVI alone cannot construct an efficient metric to see the spatial patterns of water stress at ecosystem level unless they are coupled with water status of vegetation at that moment. This study hypothesizes that a metric which can combine LST-NDVI information with an indicator for canopy water status could give more accurate estimations of the real-time vegetation water stress. The remotely sensed plant canopy water status indicator (a metric based on canopy reflection in the Short-Wave Infrared region (SWIR)) could add the canopy water status information to the LST-NDVI based indices, which may better explain spatial/temporal water stress condition in the plants especially in densely forested areas where signal saturation is a major issue. In this study, the third-dimensional information of SWIR has been combined with LST-NDVI spectral space to create a new remotely sensed vegetation water stress index, TVWSI (Temperature Vegetation Water Stress Index) which seems to be more realistic to capture stress dynamics at large scale.&#160;Sixty grids (2 km X 2 km) each containing 16 pixels of daily MODIS-reflectance (band 1 &#8211; band 7, 500 m spatial resolution) and 4 pixels of daily MODIS-LST (1 km spatial resolution) were chosen over forested areas in Victoria representing most of the bioregions as classified by the Interim Biogeographic Regionalisation for Australia (IBRA7). From 2002 to 2018 daily TVWSI values of each grid were evaluated against the modelled daily available soil moisture content in the top 1 m of the soil profile, and rainfall data, from the Australian Bureau of Meteorology (BOM). TVWSI performed better than other dryness indices mentioned in the literature. A high correlation was obtained between TVWSI vs. soil moisture and TVWSI vs. rainfall with a coefficient of determination value of 0.6 (p<0.001) and 0.61 (p<0.001) respectively when data were combined spatially and temporally. Even improved correlations ranging (0.4-0.7, p<0.001) were obtained for individual grids over the mentioned period. While correlation ranging (0.15-0.48, p<0.001) were obtained using dryness indices like Perpendicular Drought Index (PDI), Modified PDI (MPDI), Temperature Vegetation Dryness Index (TVDI) and Vegetation Supply Water Index (VSWI). The result shows that the TVWSI can capture real-time ecosystem water stress well and the metric could be an efficient input parameter for many hydrological, drought and fire prediction models.&#160;

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Tomato water stress index as a function of irrigation depths

Revista Brasileira de Engenharia Agrícola e Ambiental ◽

10.1590/1807-1929/agriambi.v22n2p95-100 ◽

2018 ◽

Vol 22 (2) ◽

pp. 95-100 ◽

Cited By ~ 5

Author(s):

Cícero J. da Silva ◽

César A. da Silva ◽

Carlos A. de Freitas ◽

Adelmo Golynski ◽

Luiz F. M. da Silva ◽

...

Keyword(s):

Water Stress ◽

Water Status ◽

Block Design ◽

Canopy Temperature ◽

Physical Contact ◽

Stress Index ◽

Tomato Crop ◽

Industrial Processing ◽

Water Stress Index ◽

Randomized Block Design

ABSTRACT Infrared thermometry allows evaluating plants under water stress, by measuring the canopy temperature, without the need of physical contact with the leaves. The aim of this study was to determine the water stress index of the tomato crop for industrial processing (Hybrid ‘BRS Sena’), as a function of irrigation depths applied by subsurface drip irrigation, in Southern Goiás, Brazil, in 2015 and 2016. The experiment was conducted in a randomized block design, with four replicates. The treatments consisted in five irrigation depths: 50, 75, 100, 125 and 150% of crop evapotranspiration. The water stress index of the tomato crop was evaluated using two methodologies, as a function of the canopy temperature, air temperature and other local meteorological parameters, as well as the relationship between water stress index and crop yield. Theoretical and empirical methods estimate CWSI similarly in tomato. In the hottest hours of the day, even under adequate soil moisture conditions, the ‘BRS Sena’ tomato showed CWSI above 0.2. CWSI is a good indicator to evaluate the water status of the tomato crop for industrial processing and to recommend the moment of irrigation. The higher the CWSI, the lower the yield of ‘BRS Sena’ tomato.

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Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica

Agronomy ◽

10.3390/agronomy11112244 ◽

2021 ◽

Vol 11 (11) ◽

pp. 2244

Author(s):

Mingxin Yang ◽

Peng Gao ◽

Ping Zhou ◽

Jiaxing Xie ◽

Daozong Sun ◽

...

Keyword(s):

Water Stress ◽

Random Forest ◽

Water Status ◽

Canopy Temperature ◽

Random Forest Model ◽

Stress Index ◽

Crop Water ◽

Crop Water Stress Index ◽

Forest Model ◽

Water Stress Index

The determination of crop water status has positive effects on the Chinese Brassica industry and irrigation decisions. Drought can decrease the production of Chinese Brassica, whereas over-irrigation can waste water. It is desirable to schedule irrigation when the crop suffers from water stress. In this study, a random forest model was developed using sample data derived from meteorological measurements including air temperature (Ta), relative humidity (RH), wind speed (WS), and photosynthetic active radiation (Par) to predict the lower baseline (Twet) and upper baseline (Tdry) canopy temperatures for Chinese Brassica from 27 November to 31 December 2020 (E1) and from 25 May to 20 June 2021 (E2). Crop water stress index (CWSI) values were determined based on the predicted canopy temperature and used to assess the crop water status. The study demonstrated the viability of using a random forest model to forecast Twet and Tdry. The coefficients of determination (R2) in E1 were 0.90 and 0.88 for development and 0.80 and 0.77 for validation, respectively. The R2 values in E2 were 0.91 and 0.89 for development and 0.83 and 0.80 for validation, respectively. Our results reveal that the measured and predicted CWSI values had similar R2 values related to stomatal conductance (~0.5 in E1, ~0.6 in E2), whereas the CWSI showed a poor correlation with transpiration rate (~0.25 in E1, ~0.2 in E2). Finally, the methodology used to calculate the daily CWSI for Chinese Brassica in this study showed that both Twet and Tdry, which require frequent measuring and design experiment due to the trial site and condition changes, have the potential to simulate environmental parameters and can therefore be applied to conveniently calculate the CWSI.

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A Theoretical Model Research of Rice Water Stress Index Based on Automated Infrared Thermal Imaging

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.712-715.433 ◽

2013 ◽

Vol 712-715 ◽

pp. 433-438 ◽

Cited By ~ 1

Author(s):

Ming Chao Cao ◽

Wen Zhong Zhang ◽

Ya Dong Han ◽

Chen Yao ◽

Yi Tao Wang ◽

...

Keyword(s):

Water Stress ◽

Theoretical Model ◽

Infrared Imaging ◽

Water Status ◽

Canopy Temperature ◽

Stomatal Resistance ◽

Stress Index ◽

Infrared Thermal Imaging ◽

Water Stress Index ◽

Rice Water

It detected the canopy temperature of rice via automated infrared imaging technology in the test under different irrigation condition, and used theCWSItheoretical model to diagnose whether the crop suffered water stress or not. It also analyzed the water stress index theoretical model of crop and other indexes on reflecting the water status of crop, including the relationship between theCWSIand leaf stomatal resistance, theCWSIand leaf net photosynthetic rate, and theCWSIand the soil moisture content. The results showed that the relations between the surface theoretical model and the above indexes were fine. It meant theCWSIwell reflected the features of water stress of rice.

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Assessing the Water-Stress Baselines by Thermal Imaging for Irrigation Management in Almond Plantations under Water Scarcity Conditions

Water ◽

10.3390/w12051298 ◽

2020 ◽

Vol 12 (5) ◽

pp. 1298

Author(s):

Saray Gutiérrez-Gordillo ◽

Iván Francisco García-Tejero ◽

Víctor Hugo Durán Zuazo ◽

Amelia García Escalera ◽

Fernando Ferrera Gil ◽

...

Keyword(s):

Water Stress ◽

Thermal Imaging ◽

Water Status ◽

Irrigation Management ◽

Irrigation Treatment ◽

Canopy Temperature ◽

Irrigation Scheduling ◽

Stress Index ◽

Crop Water ◽

Crop Water Stress Index

This work examines the use of thermal imaging to determine the crop water status in young almond trees under sustained deficit irrigation strategies (SDIs). The research was carried out during two seasons (2018–2019) in three cultivars (Prunus dulcis Mill., cvs. Guara, Lauranne, and Marta) subjected to three irrigation treatments: a full irrigation treatment (FI) at 100% of irrigation requirements (IR), and two SDIs that received 75% and 65% of the IR, respectively. Crop water monitoring was done by measurements of canopy temperature, leaf water potential (Ψleaf), and stomatal conductance. Thermal readings were used to define the non-water-stress baselines (NWSB) and water-stress baselines (WSB) for each treatment and cultivar. According to our findings, Ψleaf was the most responsive parameter to reflect differences in almond water status. In addition, NWSB and WSB allowed the determination of the crop water-stress index (CWSI) and the increment of canopy temperature (ITC) for each SDI treatment, obtaining threshold values of CWSI (0.12–0.15) and ITC (~1 °C) that would ensure maximum water savings by minimizing the effects on yield. The findings highlight the importance of determining the different NWSB and WSB for different almond cultivars and its potential use for proper irrigation scheduling.

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Monitoring Crop Water Status and Irrigation Needs Using Multispectral Airborne Sensors

HortScience ◽

10.21273/hortsci.30.4.905d ◽

1995 ◽

Vol 30 (4) ◽

pp. 905D-905

Author(s):

Thomas R. Clarke ◽

M. Susan Moran

Keyword(s):

Water Stress ◽

Near Infrared ◽

Water Status ◽

Canopy Cover ◽

Stress Index ◽

Crop Water ◽

Vegetative Cover ◽

Crop Water Stress Index ◽

Water Stress Index ◽

Subsurface Drip

Water application efficiency can be improved by directly monitoring plant water status rather than depending on soil moisture measurements or modeled ET estimates. Plants receiving sufficient water through their roots have cooler leaves than those that are water-stressed, leading to the development of the Crop Water Stress Index based on hand-held infrared thermometry. Substantial error can occur in partial canopies, however, as exposed hot soil contributes to deceptively warm temperature readings. Mathematically comparing red and near-infrared reflectances provides a measure of vegetative cover, and this information was combined with thermal radiance to give a two-dimensional index capable of detecting water stress even with a low percentage of canopy cover. Thermal, red, and near-infrared images acquired over subsurface drip-irrigated cantaloupe fields demonstrated the method's ability to detect areas with clogged emitters, insufficient irrigation rate, and system water leaks.

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Estimation water status of the vineyard by calculating multispectral index from satellite images

10.5194/egusphere-egu21-2187 ◽

2021 ◽

Author(s):

Marta Rodríguez-Fernández ◽

María Fandiño ◽

Xesús Pablo González ◽

Javier J. Cancela

Keyword(s):

Water Stress ◽

Water Potential ◽

Spectral Index ◽

Satellite Images ◽

Irrigation System ◽

Water Status ◽

Stress Index ◽

Stem Water Potential ◽

Stem Water ◽

Water Potential Measurements

The estimation of the water status in the vineyard, is a very important factor, in which every day the winegrowers show more interest since it directly affects the quality and production in the vineyards. The situation generated by COVID-19 in viticulture, adds importance to tools that provide information of the hydric status of vineyard plants in a telematic way.In the present study, the stem water potential in the 2018 and 2019 seasons, is analysed in a vineyard belonging to the Rias Baixas wine-growing area (Vilagarcia de Arousa, Spain), with 32 sampling points distributed throughout the plot, which allows the contrast and validation with the remote sensing methodology to estimate the water status of the vineyard using satellite images.The satellite images have been downloaded from the Sentinel-2 satellite, on the closets available dates regarding the stem water potential measurements, carried out in the months of June to September, because this dates are considered the months in which vine plants have higher water requirements.With satellite images, two spectral index related to the detection of water stress have been calculated: NDWI (Normalized Difference Water Index) and MSI (Moisture Stress Index). Stem water potential measurements, have allowed a linear regression with both index, to validate the use of these multispectral index to determine water stress in the vineyard.Determination coefficients of r2=0.62 and 0.67, have been obtained in July and August 2018 and 0.54 in June of 2019 for the NDWI index, as well as values of 0.53 and 0.63 in July 2018 and June 2019 respectively, when it has been analysed the MSI index.Between both seasons, the difference observed, that implies slightly greater water stress in 2019, is reflected in the climate conditions during the summer months, with an average accumulated rainfall that doesn&#8217;t exceed 46 mm of water. Although, the NDWI index has allowed to establish better relationships in the 2018 season respect to the MSI index and the 2019 season, (r2=0.60 NDWI in 2018), as well as greater differences in terms of water stress presented in the vineyard.With the spectral index calculated, it has been possible to validate the use of these index for the determination of the water stress of the vineyard plants, as an efficient, fast and less expensive method, which allows the application of an efficient irrigation system in the vineyard.

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Water stress indices for the sugarcane crop on different irrigated surfaces

Revista Brasileira de Engenharia Agrícola e Ambiental ◽

10.1590/1807-1929/agriambi.v20n10p925-929 ◽

2016 ◽

Vol 20 (10) ◽

pp. 925-929 ◽

Cited By ~ 3

Author(s):

Rodrigo G. Brunini ◽

José E. P. Turco

Keyword(s):

Water Stress ◽

Raw Materials ◽

Irrigation System ◽

Canopy Temperature ◽

Ambient Air ◽

Saccharum Officinarum ◽

Stress Index ◽

Stress Indices ◽

Sugarcane Crop ◽

Water Stress Index

ABSTRACT Sugarcane (Saccharum officinarum L.) is a crop of vital importance to Brazil, in the production of sugar and ethanol, power generation and raw materials for various purposes. Strategic information such as topography and canopy temperature can provide management technologies accessible to farmers. The objective of this study was to determine water stress indices for sugarcane in irrigated areas, with different exposures and slopes. The daily water stress index of the plants and the water potential in the soil were evaluated and the production system was analyzed. The experiment was carried out in an “Experimental Watershed”, using six surfaces, two horizontal and the other ones with 20 and 40% North and South exposure slopes. Water stress level was determined by measuring the temperatures of the vegetation cover and the ambient air. Watering was carried out using a drip irrigation system. The results showed that water stress index of sugarcane varies according to exposure and slope of the terrain, while areas whose water stress index was above 5.0 oC had lower yield values.

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